Abstract
Due to the development of information and network technologies, idle computers all over the world can be organized and utilized to enhance the overall computation performance. Grid computing refers to the combination of computer resources from multiple administrative domains used to reach a common goal. Grids offer a way of using the information technology resources optimally inside an organization. As the grid environments facilitate distributed computation, the scheduling of grid jobs has become an important issue. This study introduces a novel approach based on Biogeography Based Optimization algorithm (BBO) for scheduling jobs on computational grid. The proposed approach generates an optimal schedule so as to complete the jobs within a minimum period of time. The performance of the proposed algorithm has been evaluated with Genetic Algorithm (GA), Differential Evolution algorithm (DE), Ant Colony Optimization algorithm (ACO) and Particle Swarm Optimization algorithm (PSO).
Highlights
Grid computing is a form of distributed computing that involves coordinating and sharing computing, application, data and storage or network resources across dynamic and geographically dispersed organization (Foster and Kesselmann, 2004)
In this study we introduce a novel approach based on Biogeography Based optimization for scheduling jobs on computational grid
This study presents a novel grid job scheduling approach based on Biogeography Based Optimization algorithm (BBO) algorithm to optimize the makepan and flowtime
Summary
Grid computing is a form of distributed computing that involves coordinating and sharing computing, application, data and storage or network resources across dynamic and geographically dispersed organization (Foster and Kesselmann, 2004). It has been applied to real-world optimization problems, including sensor selection (Simon, 2008), economic load dispatch problem (Bhattacharya and Chattopadhyay, 2010), satellite image classification (Panchal et al, 2009), rectangular micro strip antenna design (Lohokare et al, 2009), design of Yagi-Uda Antenna (Singh et al, 2010), traveling salesman problem (Song et al, 2010) and robot controller tuning (Lozovyy et al, 2011) This is a pioneer effort in the research area of Grid scheduling, which makes use of Biogeography Based optimization technique to dynamically generate an optimum schedule so as to complete the tasks within a minimum period of time as well as utilizing the resources in an efficient way
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